As is known in the art, medical, life science and biotechnology experiments typically produce large amounts of digital information and digital images. Such experiments include study in disciplines such as genomics, proteomics, pharmacogenomics, molecular imaging, diagnostic medical imaging includes histopathology, cell-cycle analysis, genetics, magnetic resonance imaging (MRI), digital x-ray and computed tomography (CT). Converting large amounts raw data including raw data on digital images generated in these experiments into meaningful information that can be used by an analyst to formulate an opinion remains a challenge that hinders many investigators.
As is known in the art, genomics is the study of genomes, which includes genome mapping, gene sequencing and gene function. Gene expression microarrays are revolutionizing the biomedical sciences. A DNA microarray consists of an orderly arrangement of DNA fragments representing the genes of an organism. Each DNA fragment representing a gene is assigned a specific location on the array, usually a glass slide, and then microscopically spotted (<1 mm) to that location. Through the use of highly accurate robotic spotters, over 30,000 spots can be placed on one slide, allowing molecular biologists to analyze virtually every gene present in a genome. A complementary DNA (cDNA) array is a different technology using the same principle; the probes in this case are larger pieces of DNA that are complementary to the genes one is interested in studying. High-throughput analysis of micro-array data requires efficient frame work and tools for analysis, storage and archiving voluminous image data. For more information see “DNA Microarrays. History and overview” by E. M. Southern, Methods Molecular Biology Journal, 170: 1-15, 2001.
As is known in the art, proteomics is the study of the function of expressed proteins and analysis of complete complements of proteins. Proteomics includes the identification and quantification of proteins, the determination of their localization, modifications, interactions, activities, and, ultimately, their function. In the past proteomics is used for two-dimensional (2D) gel electrophoresis for protein separation and identification. Proteomics now refers to any procedure that characterizes large sets of proteins.
Rapid growth of this field is driven by several factors—genomics and its revelation of more and more new proteins; powerful protein technologies, such as newly developed mass spectrometry approaches, global two-hybrid techniques, and spin-offs from DNA arrays. See for example, “From genomics to proteomics,” by M. Tyers and M. Mann in Nature Journal 2003, 13:422(6928):203-7. Large-scale data sets for protein-protein interactions, organelle composition, protein activity patterns and protein profiles in cancer-patients are generated in the past few years. Rapid analysis of these data sets requires innovative information driven framework and tools to process, analyze, and interpret prodigious amounts of data.
Tissuemicroarrays (TMA) work on the similar principles of DNA microarrays where large number of tissue samples are placed on a single slide and analyzed for these expression of proteins. The image data generated in such cases is tremendous and require efficient software analysis tools. TMA analysis involves reporting protein to be detected by immunohistochemical (IHC), immunofluorescence, luminescence, absorbance, and reflection detection.
As is known in the art, pharmacogenomics is the field of investigation that aims to elucidate the inherited nature of inter-individual differences in drug disposition and effects, with the ultimate goal of providing a stronger scientific basis for selecting the optimal drug therapy and dosages for each patient. There is great heterogeneity in the way humans respond to medications, often requiring empirical strategies to find the appropriate drug therapy for each patient. There has been great progress in understanding the molecular basis of drug action and in elucidating genetic determinants of disease pathogenesis and drug response. These genetic insights should also lead to mechanism-based approaches to the discovery and development of new medications. See, for example, “Pharmacogenomics: Unlocking the Human Genome for Better Drug Therapy,” by Howard L. McLeod, William E. Evans in Annual Review of Pharmacology and Toxicology 2001, Vol. 41: 101-121. Collection, analysis and maintenance of inter-individual differences data sets requires efficient information driven framework and tools to process, analyze, and interpret prodigious amounts of data.
Microscopy and molecular imaging include the identification of changes in the cellular structures indicative of disease remains the key to the better understanding in medicinal science. Microscopy applications as applicable to microbiology (e.g., gram staining), Plant tissue culture, animal cell culture (e.g. phase contrast microscopy), molecular biology, immunology (e.g. ELISA), cell biology (e.g., immunofluorescence, chromosome analysis) Confocal microscopy: Time-Lapse and Live Cell Imaging, Series and Three-Dimensional (3D) Imaging. The advancers in confocal microscopy have unraveled many of the secrets occurring within the cell and the transcriptional and translational level changes can be detected using fluorescence markers. One advantage of the confocal approach results from the capability to image individual optical sections at high resolution in sequence through a specimen. Framework with tools for 3D analysis of thicker sections, differential color detection, fluorescence in situ hybridization (FISH) etc., is needed to expedite the progress in this area.
Near infrared (NIR) multiphoton microscopy is becoming a novel optical tool for fluorescence imaging with high spatial and temporal resolution, diagnostics, photochemistry and nanoprocessing within living cells and tissues. NIR lasers can be employed as the excitation source for multifluorophor multiphoton excitation and hence multicolour imaging. In combination with FISH, this novel approach can be used for multi-gene detection (multiphoton multicolour FISH). See, for example, “Multiphoton microscopy in life sciences” by Konig K. in Journal of Microscopy, 2000, Vol. 200 (Part 2):83-104.
In-vivo imaging: Animal models of cancer are inevitable in studies that are difficult or impossible to perform in people. Imaging of in-vivo markers permit observations of the biological processes underlying cancer growth and development. Functional imaging—the visualization of physiological, cellular, or molecular processes in living tissue—would allows to study metabolic events in real time, as they take place in living cells of the body.
Diagnostic medical imaging: Imaging technology has broadened the range of medical options in exploring untapped potential for cancer diagnosis. X-ray mammography already has had a lifesaving effect in detecting some early cancers. Computed tomography (CT) and ultrasound permit physicians to guide long, thin needles deep within the body to biopsy organs, often eliminating the need for an open surgical procedure. CT scan images can reveal whether a tumor has invaded vital tissue, grown around blood vessels, or spread to distant organs; important information that can help guide treatment choices. Three dimensional image reconstruction and visualization techniques require significant processing capabilities using smaller, faster, and more economical computing solutions.
Histopathology is a very visual science. For example, cancers grow in recognizable patterns that allow for their automated identification. A breast cancer melanoma has a certain growth pattern that differs from a carcinoma of the prostate. Benign conditions also have patterns. Skin rashes, for example, are diagnosed by a combination of a type of inflammatory cells and location in the skin, that is, whether the inflammation is around blood vessels, within the epidermis, scattered, etc.
In the field of Histopathology including oncology, the detection, identification, quantification and characterization of cells of interest, such as cancer cells, through testing of biological samples is an important aspect of experimentation. Typically, a tissue sample is prepared by staining the tissue with dyes to identify cells of interest.
Examination of biological tissues typically has been performed manually by either a lab technician or a pathologist or a life science and biotechnology researcher. In the manual method, a slide prepared with a biological sample is viewed at a low magnification under a microscope to visually locate candidate cells of interest. Those areas of the slide where cells of interest are located are then viewed at a higher magnification to confirm those objects as cells of interest, such as tumor or cancer cells.
Diagnostic methods in pathology carry out the detection, identification, quantification and characterization of cells of interest. For example, in oncology, detection of cancer cells can be done by various methods, such as contrast enhancement by different dyes or by using a specific probe such an monoclonal antibody that reacts with component of cells of interest or by probes that are specific for nucleic acids.
In the last few years, slides with stained biological samples are photographed to create digital images from the slides. Digital images are typically obtained using a microscope and capturing a digital image of a magnified biological sample.
The ability to detect, through imaging, the histopathological image data for the molecular and phenotypic changes associated with a tumor cell will enhance pathologists ability to detect and stage tumors, select appropriate treatments, monitor the effectiveness of a treatment, and determine prognosis.
Cancer is an especially pertinent target of micro-array technology due to the well-known fact that this disease causes, and may even be caused by, changes in gene expression. Micro-arrays are used for rapid identification of the genes that are turned on and the genes that are turned off in tumor development, resulting in a much better understanding of the disease. For example, if a gene that is turned on in that particular type of cancer is discovered, it may be targeted use in cancer therapy.
Today, therapies that directly target malfunctioning genes are already in use and showing exceptional results. Micro-arrays are also used for studying gene interactions including the patterns of correlated loss and increase of gene expression. Gene interactions are studied during drug design and screening. Large number of gene interactions studied during a drug discovery requires efficient frame work and tools for analysis, storage and archiving voluminous image data.
A standard test used to measure protein expression is immunohistochemistry (IHC). Analyzing the tissue samples stained with IHC reagents has been the key development in the practice of pathology. Normal and diseased cells have certain physical characteristics that can be used to differentiate them from each other. These characteristics include complex patterns, rare events, and subtle variations in color and intensity.
Cancers of the epithelial cells are the most common cancers, about 90% of the total cancers diagnosed. Therefore, identification of epithelial cells in a given digital image is a first step towards an actual identification of a cancer marker being searched for. For example, identification of ER/PR, Her2, or other markers in the breast cancer tissues. In breast cancer tissues, one specific marker searched for is ER/PR, present only in epithelial cells. Thus, a first step is to identify an epithelial part of a tissue sample. A pathologist, because of years of experience immediately differentiates an epithelial part of a tissue sample from a stromal part and looks for a specific marker. However, for a method to work on identification of a specific marker in the given tissue, it is essential to identify and differentiate the epithelial cell areas from the non-epithelial cell areas.
The importance of differentiating epithelial cell areas in a digital has multiple applications. Apart from identifying a cancer, it is critical to distinguish invasive carcinomas (IC) from noninvasive lesions. Since, cancer is life threatening when it becomes invasive, it carries a potential for spreading and metastasis. Therefore an accurate diagnosis of a presence, or absence of stromal invasion is essential.
Identification of the epithelial cell areas of a given digital image is a first step towards an automation of an entire pathological analysis through microscopy and would help in the applications such as, Nuclear pleomorphism. Mitotic Count, Tubule formation, Detection of markers stained by IHC, etc.
Cancer identification in human is possible in part because of differential staining of tissue samples achieved by specific methods of staining such as Haematoxylin and Eosin (H/E) staining. Hematoxillin and Eosin (H/E) method of staining is used to study the morphology of tissue samples. Based on the differences and variations in the patterns from the normal tissue, a type of cancer is determined. Also the pathological grading or staging of cancer (Richardson and Bloom Method) is determined using the H/E staining. This pathological grading of cancer is not only important from diagnosis angle but has prognosis value attached to it
As is known in the medical arts, an over expression of proteins can be used to indicate the presence of certain medical diseases. For example, in approximately 20%-30% patients with breast cancer, tumor cells show an amplification and/or over expression of human epidermal receptor-2 (HER-2), a tyrosine kinase receptor. HER-2 is a human epidermal growth factor receptor, which is also known as c-erbB-2/neu. HER-2/neu (C-erbB2) is a proto-oncogene that localizes to chromosome 17q. Protein product of this gene is typically over-expressed in breast cancers. This over expression in majority of cases (e.g., 90%-95%) is a direct result of gene amplification. Over expression of HER-2/neu protein thus has prognostic significance for mammary carcinoma.
Clinical studies in patients with breast cancer over the last decade have convincingly demonstrated that amplification/over expression of HER-2/neu is associated with a poor medical prognosis. Approximately 20%-30% of invasive breast carcinomas are HER-2/neu amplified. It has also been shown to be increased in a variety of other human malignancies including that of kidney, bladder and ovary. Gene amplification of HER-2/neu is associated with aggressive cell behavior and poor prognosis.
The presence of HER-2 over expression is associated with more aggressive forms of cancer (found in 25% to 30% of breast cancers). Therefore determination of HER-2 overexpression is a predictive factor in the therapy of breast cancer. HER-2 overexpression was shown to signify resistance to cyclophosphamide/methotrexate/5-fluoracil therapy and tamoxifen therapy. Also higher sensitivity to the high doses of anthracycline containing regimens has been observed.
Normal epithelial cells typically contain two copies of the HER-2/neu gene and express low levels of HER-2/neu receptor on the cell surface. In some cases, during oncogenic transformation the number of gene copies per cell is increased, leading to an increase in messenger Ribonucleic Acid (mRNA) transcription and a 10- to 100-fold increase in the number of HER-2/neureceptors on the cell's surface, called overexpression.
In general, the presence of HER-2/neu overexpression appears to be a key factor in malignant transformation and is predictive of a poor prognosis in breast cancer. A standard test used to measure HER-2/neu protein expression is IHC. IHC has been specifically adapted for detection of HER-2/neu protein using specific antibodies. As seen with most of the histopathological analysis, there is inter-laboratory variation in HER-2/neu overexpression scoring due to subjective measures of staining intensity and pattern. It is widely acknowledged that the ideal test for HER-2 status is one that is simple to perform, specific, sensitive, standardized, stable over time, and allows archival tissue to be assayed. At present the test that best meets these criteria is IHC.
Evaluation of HER-2/neu has become all the more important with the development of Herceptin® (i.e., trastuzamab package insert) which directly targets the HER-2/neu protein and appears to be useful in late stage metastatic adenocarcinoma of the breast. Thus, the evaluation of HER-2/neu is clinically important for at least two things; the first is, as a predictive marker for response to Herceptin® therapy and the second is, as a prognostic marker. Analysis of HER-2/neu amplification is the sole criteria for treatment with Herceptin. To summarise, accurate detection of HER-2/neu amplification is important in the prognosis and selection of appropriate therapy and prediction of therapeutic outcome.
Prostate cancer (i.e., prostate adenocarcinoma) has become an important concern in terms of public health these past fifteen years internationally as well. A recent French epidemiological study revealed 10,104 deaths due to this disease in 2000 (See Fournier G, Valeri A, Mangin P, Cussenot O. Prostate cancer: Epidemiology, Risk factors, Pathology. Ann Urol (Paris). October 2004; 38(5):187-206). In 2001, there were 30,142 new cases of prostate cancer diagnosed in the UK (See info.cancerresearchuk.org/cancerstats/prostate/incidence/). The American Cancer Society (ACS) estimates that about 230,900 new cases will be diagnosed in 2004 and about 29,900 men will die of the disease. (See urologychannel.com/prostate/cancer/index.shtml).
A little-known fact is that a man is 33% more likely to develop prostate cancer than an American woman is to get breast cancer. (See www.prostatecancerfoundation.org). Prostate cancer strikes as many men (and causes almost as many deaths annually) as breast cancer does in women, but lacks the national awareness and research funding breast cancer currently receives.
Only a biopsy can definitely confirm prostate cancer. Typically, the physician takes multiple tissue samples for biopsy. Instead of doing the classic right and left prostate biopsies and put them into two specimen jars, more and more urologists are now using 12 jars for multiple tissue sample cores (or at least greater than 8 biopsy cores). This new approach, so-called ‘extended prostate biopsy procedure’, improved the cancer detection rate and many cancers can be detected earlier. But, it adds more work to histopathologists in the usual manual screening of those slides.
Diagnostic methods in pathology carry out the detection, identification, quantitation and characterization of cells of interest. For example, in oncology, detection of cancer cells can be done by various methods, such as contrast enhancement by different dyes or by using a specific probe such an monoclonal antibody that reacts with component of cells of interest or by probes that are specific for nucleic acids.
IHC is a technique that detects specific antigens present in the target cells by labeling them with antibodies against them which are tagged with enzymes such as alkaline phosphatase or horseradish peroxidase (HRP) to convert a soluble colorless substrate to a colored insoluble precipitate which can be detected under the microscope. Enzyme-conjugated secondary antibodies help visualize the specific staining after adding the enzyme-specific substrate. Tissue labeled with antibodies tagged to HRP shows a brown colour deposited because of conversion of substrate of 3′,3-diaminobenzidine tetrahydrochloride (DAB) by HRP. It gets localized at the site where the marker is expressed in the cell. For example, HER-2/neu is localized at the cell membrane marking the cell membrane completely or partially. To enhance the contrast cells are counterstained with haematoxylin which stains the nuclei blue-black.
With standardization of laboratory testing and appropriate quality control in place, the reliability of IHC will be improved further. Though a more sensitive reproducible and reliable method for detection of HER-2/neu amplification at gene level is fluorescence in situ hybridization (FISH), IHC remains the most common and economical method for HER-2/neu analysis.
In the field of medical diagnostics including oncology, the detection, identification, quantification and characterization of cells of interest, such as cancer cells, through testing of biological samples is an important aspect of diagnosis. Typically, a tissue sample is prepared by staining the tissue with dyes to identify cells of interest.
Examination of biological tissues typically has been performed manually by either a lab technician or a pathologist. In the manual method, a slide prepared with a biological sample is viewed at a low magnification under a microscope to visually locate candidate cells of interest. Those areas of the slide where cells of interest are located are then viewed at a higher magnification to confirm those objects as cells of interest, such as tumor or cancer cells.
In the last few years, slides with stained biological samples are photographed to create digital images from the slides. Digital images are typically obtained using a microscope and capturing a digital image of a magnified biological sample.
A digital image typically includes an array, usually a rectangular matrix, of pixels. Each “pixel” is one picture element and is a digital quantity that is a value that represents some property of the image at a location in the array corresponding to a particular location in the image. Typically, in continuous tone black and white images the pixel values represent a “gray scale” value.
Pixel values for a digital image typically conform to a specified range. For example, each array element may be one byte (i.e., eight bits). With one-byte pixels, pixel values range from zero to 255. In a gray scale image a 255 may represent absolute white and zero total black (or visa-versa).
Color images consist of three color planes, generally corresponding to red, green, and blue (RGB). For a particular pixel, there is one value for each of these color planes, (i.e., a value representing the red component, a value representing the green component, and a value representing the blue component). By varying the intensity of these three components, all colors in the color spectrum typically may be created.
However, many images do not have pixel values that make effective use of the full dynamic range of pixel values available on an output device. For example, in the eight-bit or byte case, a particular image may in its digital form only contain pixel values that fall somewhere in the middle of the gray scale range. Similarly, an eight-bit color image may also have RGB values that fall within a range some where in middle of the range available for the output device. The result in either case is that the output is relatively dull in appearance.
The visual appearance of an image can often be improved by remapping the pixel values to take advantage of the full range of possible outputs. That procedure is called “contrast enhancement.” While many two-dimensional images can be viewed with the naked eye for simple analysis, many other two-dimensional images must be carefully examined and analyzed. One of the most commonly examined/analyzed two-dimensional images is acquired using a digital camera connected to an optical microscope.
One type of commonly examined two-dimensional digital images is digital images made from biological samples including cells, tissue samples, etc. Such digital images are commonly used to analyze biological samples including a determination of certain knowledge of medical conditions for humans and animals. For example, digital images are used to determine cell proliferate disorders such as cancers, etc. in humans and animals.
There are several problems associated with using existing digital image analysis techniques for analyzing digital images for determining know medical conditions. One problem is that existing digital image analysis techniques are typically used only for analyzing measurements of chemical compounds applied to biological samples such as groups of cells from a tissue sample. Another problem is the manual method used by pathologists is time consuming and prone to error including missing areas of the slide including tumor or cancer cells.
There have been attempts to solve some of the problems associated with manual methods for analyzing biological samples. Automated cell analysis systems have been developed to improve the speed and accuracy of the testing process. For example, U.S. Pat. No. 6,546,123 entitled “Automated detection of objects in a biological sample” that issued to McLaren, et al. teaches “A method, system, and apparatus are provided for automated light microscopic for detection of proteins associated with cell proliferative disorders.”
U.S. Patent Published Application No. 20030170703 entitled “Method and/or system for analyzing biological samples using a computer system” published by Piper et al. teaches “A method and/or system for making determinations regarding samples from biologic sources. A computer implemented method and/or system can be used to automate parts of the analysis.”
Medical oncology is entering into the arena of “customized” treatment of cancer based on the presence of molecular targets or particular patient/tumor characteristics. The fields of pharmacogenetics and pharmacogenomics are rapidly expanding. The long term view on drug development appears to indicate that therapies to treat cancer will proceed down a path of selection based upon these molecular targets. The ability to efficiently and precisely identify these targets is more critical now than ever before in the cancer therapy development process.
The genomics and proteomics revolution has left scientists with too many early-stage targets for the next generation of drug discovery efforts. It is desirable to use a molecular pathology approach to provide the pharmaceutical industry with information that allows prioritization of potential targets and selection of those with the most significance to major human diseases and easy and standardized method in allowing them to do so.
On the technology front, there is need to develop tools and methods to study the cellular structures/activities that become disturbed in the disease. Further such tools should enable drug discovery researchers in analyzing cell compartments like nucleus, cytoplasm or cell membrane of carcinoma cells. It is known that some of diacylglycerol kinases under go a translocation from the cytoplasm to the plasma membrane. The ability to automatically identify and quantify such translocations in a biopsy specimen will aid discovery research.
TMA analysis has changed the pace at which a pharmaceutical companies can discover newer drugs. One of the requirements of rapid analysis of cores from a tissue micro array is tissue independent pathological analysis. The basic aspects of cells like nucleus, cytoplasm and membrane do not vary with tissues in the sense overall histology but can vary and are present all across the tissues. Identifying these basic components of cells/tissues based on staining intensity and morphology is necessary to achieve true tissue independence for automated analysis.
There is a considerable gap between the pace at which drug discovery is progressing and automated tools available to assist the drug researcher. Often researchers are forced to resort to manual methods which are subjective, time consuming and could be inconsistent. Thus, it is desirable to provide a solution to this problem by using digital image based tissue independent simultaneous nucleus, cytoplasm and membrane quantitation.
There have been several attempts to provide quantitation of nucleus, cytoplasm or membrane individually.
For example, Zoë E Winters et al reported a study of subcellular p21WAF1/CIP1 expression in relation to HER-2 immunoreactivity in an article titled “Cytoplasmic p21WAF1/CIP1 expression is correlated with HER-2/neu in breast cancer and is an independent predictor of prognosis”. This study highlights a new pathway by which HER-2 may modify cancer behaviour. HER-2 as a predictor of poor prognosis may partly relate to its ability to influence the relocalisation of p21WAF1/CIP1 from the nucleus to the cytoplasm, resulting in a loss of p21WAF1/CIP1 tumour suppressor functions. Cytoplasmic p21WAF1/CIP1 may be a surrogate marker of functional HER-2 in vivo.
HER-2 is one of four Erb B family-type I receptor tyrosine kinases and is the preferred dimerization partner for the epidermal growth factor receptor. The Erb B receptors are important in normal development and in human cancer. HER-2, independent of its own ligand, activates other Erb B receptors to increase their ligand affinity and to amplify biological responses. HER-2 plays a key role in activating cytoplasmic signalling through the phosphatidylinositol-3 kinase (PI-3K)/protein kinase B (Akt) and mitogen-activated protein kinase pathways to influence transcription of nuclear genes. Activation of PI-3K/Akt is involved in cell proliferation and confers resistance to apoptosis. Breast cancer is associated with deregulated expression of HER-2, detectable as HER-2 amplification or protein overexpression identified in 10-40% of tumours. HER-2 expression is indicative of poor prognosis and may predict tumour responses to hormone therapy and chemotherapy. Cell cycle progression is regulated by cyclin-dependent kinases (CDKs) associated with cyclin proteins. p21WAF1/CIP1, a downstream target of p53, is a CDK inhibitor that re-enforces p53-mediated G1 and G2 arrest following genotoxic insults, to facilitate DNA repair. The integrity of G1 and G2 checkpoints requires the nuclear localisation of p21WAF1/CIP1. Recent evidence including subcellular fractionation suggests that p21WAF1/CIP1 can localise in the cytoplasm in cancer tissues and cell lines, where it inhibits apoptosis by binding and inhibiting the apoptosis signal-regulating kinase 1. Such an anti-apoptotic function in breast cancers could underlie the association between cytoplasmic p21WAF1/CIP1 and poor prognosis. Upregulation of p21WAF1/CIP1 occurs through PI-3K/Akt signalling, and may involve insulin-like growth factors, p53-dependent pathways or HER-2 expression. A HER-2-overexpressing breast cancer cell line transcriptionally upregulates p21WAF1/CIP1 and has been shown to produce its cytoplasmic localisation through a mechanism whereby Akt binds and phosphorylates p21WAF1/CIP1 in its nuclear localisation signal. In vivo HER-2 expression may involve changes in the subcellular localisation of p21WAF1/CIP1 to influence the outcome in breast cancer.
In “Dissecting the molecular mechanisms of human cancer: Translating laboratory advances into clinical practice”, A. M. Thompson, discussed the scope and limitations of various techniques used for tissue analysis. Immunohistochemsity can solve some of the problem faced by other techniques. For example in other techniques like FISH the architecture and spatial relationships of the cancer tissue to surrounding structures and whether it is the cancer tissue or the stroma or lymphocytes being examined is usually unclear. Immunohistochemistry has the advantage of demonstrating the presence of proteins and in which cells and cellular compartments the protein is present. It can be used to supplement the techniques already outlined or protein analyses such as western blotting or enzyme-linked immuno-sorbent assay (ELISA) techniques and by using a range of antibodies to a particular protein, functional associations can be implied.
In “Development and Characterization of Immunohistochemistry and Fluorescence in situ Hybridization Diagnostic Assay Kits for Use in the Selection of Patients for Treatment with a Particular Therapeutic Agent”, Susan Jerian indicated that that therapies to treat cancer will proceed down a path of selection based upon these molecular targets. The ability to efficiently and precisely identify these targets is more critical in the cancer therapy development process. Two major areas of concern expressed are: (1) the systematic and science based incorporation of molecular target assay development into anti-cancer therapy development programs and (2) the identification of information which clinicians need to know in order to select the proper testing modality and to interpret those results.
In order to approve therapies which are intended for use in patients whose tumors express a particular molecular trait (e.g. protein overexpression, gene amplification, or genetic polymorphism), the FDA, Center for Biologics Evaluation and Research (CBER) has required that the diagnostic assay for identification of that molecular trait be available to physicians either through central laboratory testing or as a Center for Devices and Radiological Health (CDRH) approved PMA (Pre-Market Approval) for a device or test kit.
Two other diagnostic techniques: (1) immunohistochemistry (IHC), a technology now widely available in most pathology laboratories, and a preferred method for identification of protein overexpression, and (2) fluorescence in situ hybridization (FISH), a technique less widely available, but rapidly becoming a preferred method for identification of gene amplification.
Difficulties are reported with the performance and interpretation of IHC and FISH in the medical oncology community over the last several years. In particular the detection of estrogen and progesterone receptors and the detection of HER2/neu targets is not consistent. Problems encountered include, but are not limited to, identification of cutoff points in assay scores to define positive vs. negative results, broad interlaboratory variability in performance of the assays, discrepancies between laboratories with high volume vs low volume throughput, use of “home brew” antibodies for IHC, deviations from recommended methods in the package insert leading to altered performance characteristics of the assays, conflicting data in the published literature, and lack of data from prospectively conducted studies.
There are several problems associated with using existing digital image analysis techniques for analyzing FISH images. 1) there is need to image specimen slides at a very high resolution to count small fluorescent signals. Once there are a large number of image sections to be processed together, issues like seamless composition of tiles becomes an issue. 2) Further, one needs to prepare a separate slide and capture images through fluorescent microscope. 3) Another problem with FISH based analysis is the need to stack planes in three dimensions to get a focused image. Otherwise, the small fluorescent signals far below the surface of the tissue will give weak, blurred ring of fluorescent signals. 4) Immunohistochemistry is preferable to FISH as primary test for HER-2.because FISH testing is more costly and more time consuming, they suggest that immunohistochemistry should be the method of choice, with FISH reserved for specimens with indeterminate results. Failure to obtain interpretable results after two test runs occurred in 5.0% of samples tested by FISH and 0.08% of those tested by immunohistochemistry. 5) FISH is more expensive, the reports indicate, with reagent costs averaging $140 compared with $10 for immunohistochemistry. Procedure time and interpreting time by the pathologist are both about nine times higher for FISH. 6) FISH can be carried out with fresh tissues and frozen tissues but not with specimens or cores in a TMA.
Elizabeth L. Wiley and Leslie K. Diaz commented that “the combined use of FISH and immunohistochemistry will achieve more accuracy and clinical efficacy than the use of either test alone,” in a related editorial. Gown's group recommended a testing algorithm for HER-2 determination in which primary screening is performed with immunohistochemistry. FISH would then be required for the approximately 15% of samples with indeterminate (2+) immunohistochemistry scores.
In U.S. Pat. No. 6,800,283 entitled “Isolated human casein kinase proteins, nucleic acid molecules encoding human casein kinase proteins, and uses thereof,” that issued to Gong, et al. teaches The present invention provides amino acid sequences of peptides that are encoded by genes within the human genome, the kinase peptides of the present invention. The present invention specifically provides isolated peptide and nucleic acid molecules, methods of identifying orthologs and paralogs of the kinase peptides, and methods of identifying modulators of the kinase peptides.”
In United States Published Patent Application 20030228694, published by Sabatini, entitled
In “Using immunohistochemistry to study plant metabolism: the examples of its use in the localization of amino acids in plant tissues, and of phosphoenolpyruvate carboxykinase (PEPCK) and its possible role in pH regulation”, illustrated two of the several potential uses of Immunohistochemistry in plant histology, namely, determination of the location of amino acids and enzymes and establishing a functional role of certain enzymes based on their location in the plant tissues. Immunohistochemistry has been widely used to localize antigens in plant tissues. The localization of enzymes by immunohistochemistry has provided valuable information about how metabolism is compartmentalized between different tissues in many plant structures such as the vasculature, developing seeds, fruit, leaves and stems and roots. An advantage of immunohistochemistry is that it reveals the location and abundance of the protein whereas visualization of mRNA by in situ hybridization may not.
Using immunohistochemistry it was found that, in many plants, PEPCK was present in tissues that are likely to be active in the metabolism of nitrogen, such as developing seeds and the vasculature, and in these it was particularly abundant in regions where metabolism of amino acids is likely to be enhanced. However, to investigate what, if any, this function might be in nitrogen metabolism required immunohistochemistry to be used in combination with other approaches.
On the website, protocol-online (www.protocol-online.org/prot/Immunology/Immunohistochemistry/) it is stated, Immunohistochemistry is a method of detecting the presence of specific proteins in cells or tissues and consists of the following steps: 1) primary antibody binds to specific antigen; 2) antibody-antigen complex is bound by a secondary, enzyme-conjugated, antibody; 3) in the presence of substrate and chromogen, the enzyme forms a colored deposit at the sites of antibody-antigen binding.
On the website (www.ihcworld.com/_protocols/general_IHC/immunoenzyme_double.htm), it is stated that this enzyme based double staining method is limited for the demonstration of two proteins at different locations. For example, one is nuclear protein, the other is cytoplasmic protein.
20/20 gene systems, Inc. (www.2020gene.com/TissueBlotKits_frame.htm) has applied Layered Gene Scanning (LGS) to the analysis of proteins in whole tissue sections. This platform is claims to preserve the two-dimensional morphology of the tissue combining this advantage of immunohistochemistry (IHC) with the high throughput and ease of use of microarrays.
IHC is also used in veterinary diagnostics. Neoplastic and infectious diseases are often the main focus of IHC in veterinary medicine. 1 Diagnosis of neoplasia. Often, the tissue origin of a tumor cannot be determined with routine histology. Using specific antibodies for different tissues or cells (e.g., cytokeratin for epithelium, vimentin for mesenchymal cells, lymphoid markers, etc); the origin of many tumors can be determined with IHC. 2 Detection of micrometastases. Early metastasis can be difficult to detect using conventional histology. IHC highlights the presence of single or small groups of neoplastic cells in metastatic sites. Early detection of micrometastases increases the chances of survival with surgical removal of affected nodes or by modification of the treatment protocol. 3 Prognostic markers. Some proteins are expressed in neoplastic, but not in normal mature cells (e.g. embryonal proteins), expressed in neoplastic cells in larger amounts than in normal cells (e.g. cycle-related proteins), or structurally modified in neoplastic cells (mutant p53 protein). These changes may have prognostic significance in specific tumor types. It has been reported recently that the immuno-histochemical detection of KIT protein in mast cell tumors of dogs has prognostic significance. We are testing some of these markers to determine their significance in veterinary cancers. 4 Diagnosis of infectious diseases. Detection of antigens of an infectious agent with IHC has etiologic significance. The advantage of IHC over microbiologic techniques is that antigen detection can be correlated with histopathologic changes and thus can confirm the significance of a particular bacterial or viral isolate obtained by other methods. The ADDL offers immunohistochemical tests for infectious diseases of small (feline herpesvirus, Leptospira, canine parvovirus, canine adenovirus, feline leukemia virus, canine distemper virus, etc) and food animals (IBR, BVD virus, TGE virus, Listeria, Cryptosporidium, Neospora, etc).
Once the images of interest are identified, multiple measurements of nuclear and cell size and shape, chromatin texture, and other spatial and photometric features can be taken automatically with the aid of fast microcomputers. These data can be interpreted by a variety of diagnostic algorithms, multivariate statistical methods, rule-based expert systems, neural networks, Bayesian-belief networks and others to arrive at automated classifications.
Biogenex has developed products for image analysis for diagnosis and screening purposes. The ChromaVision Automated Cellular Imaging System (ACIS) provides quantitation of staining intensities, percent positive nuclei and area measurements on immunohistochemically (IHC) stained tissue sections.
Applied Imagings Reasearch IHC Analysis suite contains the Hersight, Kisight and Aesight imaging modules each designed specialized for the areas of membraneous, nuclear and cytoplasmic quantification of IHC staining.
Limitation of the techniques available in prior art is the ability to identify and quantify individual cell components. There are several reasons behind this inability. The three major components of cell are nucleus, cytoplasm and membrane. Nucleus is very small compared to cell size. Cytoplasm surrounding nucleus occupies most of the cell volume. Membrane of a cell is a thin layer of fibers holding cytoplasm and nucleus in tact inside. Each of the three components can get stained or unstained or counterstained. If a component is stained it might be visible as brown. If a component is counterstained, it takes blue color. Unstained components are transparent or colorless gray. Observing a three dimensional cell in two dimensions has its own issues. A nucleus might be seen as touching membrane. There could be large variation in the sizes of cell nucleus, cytoplasm and cell itself. Simultaneous identification of components becomes complex if more than one component behaves similar. That is, if nucleus and cytoplasm take stain and appear brown red, detecting the boundary between cytoplasm and membrane is much more difficult than the case where only membrane gets stained. Similarly, it will be very difficult to locate nucleus in a cell if both nucleus and cytoplasm are stained similar. There has been some attempts to use cocktail staining to overcome some of these issues. However, cocktail staining is found to be unsuitable for some applications.
None of the existing products are capable of providing simultaneous quantitation of nucleus, cytoplasm and membrane, which is a key factor for studies of translocation.
However, these attempts still do not solve all of the problems with automated biological analysis systems that have been developed to improve the speed and accuracy of the testing process. Thus, it is desirable to provide an automated biological sample analysis system that not only provides automated analysis of biological samples based on analyzing an intensity of a chemical or biological marker, but also on the morphological features of the biological sample.